Predictive intersection search

ABSTRACT

A device can receive input indicating an intersection of two or more roads. The device can identify the two or more roads included in the input using an indicator. The device can determine a geographic location of another device using information that identifies the geographic location received from the other device. The device can identify a data structure that includes information identifying a set of intersections associated with the geographic location. The device can perform a search of the two or more roads using the information identifying the two or more roads and the information included in the data structure. The device can determine a priority for one or more results of the search for the intersection after performing the search of the two or more roads. The device can provide the one or more results of the search for the intersection to permit and/or cause an action to be performed.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/624,284, filed Jun. 15, 2017, which is incorporated herein byreference.

BACKGROUND

A web search query can include a query that a user enters into a websearch engine to obtain desired information. A web search query caninclude plain text and/or search directives to direct a manner in whicha search engine searches for information. A web search query can differfrom use of a query language, in that a query language can be governedby strict syntax rules.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1D are diagrams of an overview of an example implementationdescribed herein;

FIG. 2 is a diagram of an example environment in which systems and/ormethods, described herein, can be implemented;

FIG. 3 is a diagram of example components of one or more devices of FIG.2; and

FIG. 4 is a flow chart of an example process for predictive intersectionsearch.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings can identify the same or similar elements.

Use of a navigation system can include a search for an intersection(e.g., an intersection of two or more roads), such as to obtain a set ofdirections to the intersection. To perform a search for an intersection,a user of the navigation system can input a complete address of theintersection, such as full street names (e.g., “16th Street” rather than“16th,” “16,” “16 st.,” etc.), a location of the intersection (e.g., acity in which the intersection is located, a state in which theintersection is located, etc.), a postal code, or other identifier,associated with the intersection, such as a zip code, and/or the like.For example, the user can input an address similar to “16th street andBlake street, Anywhere, CO, 22222” to search for an intersection of 16thstreet and Blake street in a particular city in a particular state. Inaddition, when a device performs a search for the intersection, thedevice can perform individual searches for each of the roads todetermine whether the roads are associated with a geographic locationand/or can determine whether the roads associated with the intersectionactually intersect. Further, a device performing the search can lack atechnique for intelligently predicting an intersection for which theuser is searching.

This consumes processing resources of a device performing a search forthe intersection when the user does not input a complete address of theintersection via failing to successfully identify the intersectionand/or consumes time of the user by having the user identify and input acomplete address of the intersection. In addition, this reduces anefficiency of searching for an intersection via consumption ofprocessing resources and increased processing time (e.g., by performingindividual searches for each of the roads, determining whether the roadsactually intersect, etc.), by needing a complete address of theintersection (e.g., rather than intelligently predicting an intersectionfor which the user is searching), and/or the like.

Some implementations, described herein, provide a server device that iscapable of searching for an intersection using input that includes anincomplete address for the intersection (e.g., “16 and Blake,” “16th andBlake st,” “16 and B,” etc. rather than “16th street and Blake street,Anywhere, CO, 22222”). In addition, the server device can prioritizesearch results based on various factors. In this way, the server devicecan dynamically and predictively perform a search for an intersection.This conserves processing resources of the server device by increasing aflexibility of the server device to perform a search for an intersectionusing an incomplete address of the intersection. In addition, thisconserves time of the user related to performing a search for anintersection and/or increases an efficiency of performing a search foran intersection by permitting use of an incomplete address for theintersection. Further, this increases an efficiency of performing asearch for an intersection by reducing an amount of information theserver device processes and/or searches to perform the search, therebyconserving processing resources of the server device.

Further, this increases an accuracy of performing a search for anintersection via prioritization of search results based on variousfactors. Further, the device can perform a search for an intersectionwithout needing to perform individual searches for each of the roads todetermine whether the roads are associated with a geographic locationand/or to determine whether roads identified in the input actuallyintersect, thereby improving an efficiency of performing a search for anintersection and conserving processing resources of the device byreducing or eliminating a need for the server device to performparticular functions related to performing a search for an intersection.

FIGS. 1A-1D are diagrams of an overview of an example implementation 100described herein. As shown in FIG. 1A, example implementation 100 caninclude a server device and a user device. Although implementation 100shows a single user device and a single server device for explanatorypurposes, in reality, there can be thousands, millions, billions, etc.of user devices and/or server devices.

As shown by reference number 105, a user of the user device can provideinput (e.g., text input or voice input) that identifies an intersection.For example, and as further shown by reference number 105, the input caninclude an incomplete address for the intersection (e.g., “16 and b”rather than “16th Street and Blake Street, Anywhere, CO, 22222”). Insome implementations, the input can include hundreds, thousands,millions, etc. of data elements from hundreds, thousands, millions, etc.of user devices.

As further shown in FIG. 1A, and as shown by reference number 110, theserver device can receive input that indicates an intersection of two ormore roads. For example, the server device can receive the input when auser of the user device indicates that the text is to be sent to theserver device, such as by selecting a button on an interface, as theuser is inputting the text (e.g., in real-time), and/or the like.

As further shown in FIG. 1A, and as shown by reference number 115, theserver device can identify the two or more roads included in the inputusing an indicator included in the input. For example, the server devicecan identify the two or more roads in the input by identifying a term, aphrase, a symbol, and/or the like that separates each of the two or moreroads included in the input. As shown by reference number 120, whenidentifying the two or more roads, the server device can parse theinput. For example, the server device can identify a particular term,symbol, etc., such as “and” that separates input identifying each of thetwo or more roads included in the input. In this case, as shown byreference number 125, the server device can identify “16” as identifyinga first road in the input and “b” as identifying a second road in theinput based on “16” and “b” being separated by the term “and” in theinput. In this way, the server device can process input to identify twoor more roads included in the input.

As shown in FIG. 1B, and as shown by reference number 130, the serverdevice can receive geographic location information from the user device.For example, the geographic location information can include a globalpositioning system (GPS) location, an address associated with an accountassociated with the user device, input from the user of the user device,and/or the like. Additionally, or alternatively, the server device canreceive other information, such as information related to prior searchesof the user, information related to prior searches of other users ofother user devices, information identifying landmarks or notableintersections, and/or the like (e.g., from the user device, memoryresources of the server device, and/or the other server device).

As further shown in FIG. 1B, and as shown by reference number 135, theserver device can determine a geographic location of the user device.For example, the server device can determine a geographic location ofthe user device using the geographic location information received fromthe user device. As shown by reference number 140, the server device canidentify a data structure that includes information identifying a set ofintersections associated with the geographic location. For example, theserver device can identify a data structure that includes informationidentifying intersections associated with a particular city based ondetermining that the geographic location information identifies theparticular city as the geographic location of the user device. Thisconserves processing resources of the server device by permitting theserver device to focus a search to a particular geographic location,thereby reducing an amount of information the server device has tosearch to identify the intersection. In addition, this improves a searchfor an intersection by permitting the server device to more accuratelyidentify potential matches (e.g., relative to a search that is not basedon a geographic location).

As shown in FIG. 1C, and as shown by reference number 145, the serverdevice can perform a prefix match search of each of the two or moreroads identified in the input. For example, the server device can matcha prefix of each of the two or more roads identified in the input (e.g.,“16” and “b”) and a prefix of information in the data structure thatidentifies roads for a set of intersections associated with a geographiclocation.

As further shown in FIG. 1C, reference number 150 shows an example ofinformation included in a data structure that the server device cansearch. For example, the information can identify a set ofintersections, and roads associated with each intersection. As shown byreference number 155, the server device can identify a set ofintersections where a name of one of the roads begins with “16” and aname of another of the roads begins with “b” based on performing prefixmatch searches of “16” and “b.” In some implementations, when performinga search of the data structure, the server device can perform a searchof thousands, millions, etc. of intersections associated with thousands,millions, etc. of roads. In this way, the server device can perform asearch using a data set that cannot be processed manually. In this way,the server device can perform a search for an intersection associatedwith a geographic location without performing individual searches fortwo or more roads to determine whether the two or more roads areassociated with a geographic location and/or without then determiningwhether the two or more roads actually intersect. This conservesprocessing resources of the server device by reducing or eliminating aneed for the server device to perform particular operations related toperforming a search for an intersection.

As shown in FIG. 1D, and as shown by reference number 160, the serverdevice can determine a priority for one or more results of the prefixmatch search. For example, the server device can prioritize anintersection based on the user searching for the intersection athreshold quantity of times, based on other users of other user devicessearching for a particular intersection a threshold quantity of times,based on a particular intersection being identified as a landmark, basedon a distance of the intersection from the geographic location of theuser device, based on a score determined using information related to acombination of previously mentioned factors, and/or the like.

As further shown in FIG. 1D, and as shown by reference number 165, theserver device can provide the one or more results of the prefix matchsearch to the user device. For example, the server device can provideinformation for display that includes complete addresses of identifiedintersections via the user device. In some implementations, the serverdevice can provide results to hundreds, thousands, millions, etc. ofuser devices.

As shown by reference number 170, the user device can display a set ofintersections that match the input of the user. In some implementations,the intersections can be organized based on the determined priority andcan be displayed as complete addresses. For example, as shown, if theserver device determined the address “16th and Brass Street, Anywhere,CO” to have a highest priority, the user device can display all or aportion of the “16th and Brass Street, Anywhere, CO” address at the topof a list of possible intersection addresses, beneath the “16 and b”incomplete address that was input by the user. In addition, the serverdevice can dynamically update results of the search as the user of theuser device inputs additional information. For example, if the userinputs the letter “l” after the letter “b,” then the server device canremove “16th and Brass Street, Anywhere, CO” from the list of possiblematches based on the input identifying a road that begins with “bl”rather than “br.”

In this way, a server device can dynamically and predictively perform asearch for an intersection. This conserves processing resources of theserver device by increasing a flexibility of the server device toperform a search for an intersection using an incomplete address of theintersection. In addition, this conserves time of the user related toperforming a search for an intersection and/or increases an efficiencyof performing a search for an intersection by permitting use of anincomplete address for the intersection. Further, this increases anefficiency of performing a search for an intersection by reducing anamount of information the server device processes and/or searches toperform the search, thereby conserving processing resources of theserver device.

Further, this increases an accuracy of performing a search for anintersection via prioritization of search results based on variousfactors. Further, the device can perform a search for an intersectionwithout needing to perform individual searches for each of the roads todetermine whether the roads are associated with a geographic locationand/or to determine whether roads identified in the input actuallyintersect, thereby improving an efficiency of performing a search for anintersection and conserving processing resources of the device byreducing or eliminating a need for a server device to perform particularoperations related to performing a search for an intersection.

As indicated above, FIGS. 1A-1D are provided merely as an example. Otherexamples are possible and can differ from what was described with regardto FIGS. 1A-1D. For example, although implementations described withrespect to FIGS. 1A-1D use a prefix match search, other implementationscan use other types of searches, as described elsewhere herein.

FIG. 2 is a diagram of an example environment 200 in which systemsand/or methods, described herein, can be implemented. As shown in FIG.2, environment 200 can include one or more user devices 210-1 through210-N (N≥1) (hereinafter referred to collectively as “user devices 210,”and individually as “user device 210”), one or more server devices 220-1through 220-M (M≥1) (hereinafter referred to collectively as “serverdevices 220,” and individually as “server device 220”), and a network230. Devices of environment 200 can interconnect via wired connections,wireless connections, or a combination of wired and wirelessconnections.

User device 210 includes one or more devices capable of receiving,generating, storing, processing, and/or providing information associatedwith a predictive intersection search. For example, user device 210 caninclude a mobile phone (e.g., a smart phone, a radiotelephone, etc.), alaptop computer, a tablet computer, a handheld computer, a gamingdevice, a wearable communication device (e.g., a smart wristwatch, apair of smart eyeglasses, etc.), or a similar type of device. In someimplementations, user device 210 can receive input from a user thatidentifies two or more roads of an intersection and can provide theinput to server device 220 to cause server device 220 to perform asearch for an intersection using the input, as described in more detailelsewhere herein. Additionally, or alternatively, user device 210 canreceive a result of a search from server device 220, and can provide theresult for display, as described in more detail elsewhere herein. Insome implementations, there can be hundreds, thousands, millions, etc.of user devices 210.

Server device 220 includes one or more devices capable of receiving,storing, processing, generating, and/or providing information associatedwith a predictive intersection search. For example, server device 220can include a server (e.g., in a data center or a cloud computingenvironment), a data center (e.g., a multi-server micro data center), aworkstation computer, a virtual machine (VM) provided in a cloudcomputing environment, or a similar type of device. In someimplementations, server device 220 can receive input from user device210 and can perform a search to identify an intersection based on theinput, as described in more detail elsewhere herein. Additionally, oralternatively, server device 220 can provide information identifying aset of possible intersections that match the input received from userdevice 210, as described in more detail elsewhere herein. In someimplementations, there can be hundreds, thousands, millions, etc. ofserver devices 220.

Network 230 includes one or more wired and/or wireless networks. Forexample, network 230 can include a cellular network (e.g., a long-termevolution (LTE) network, a code division multiple access (CDMA) network,a 3G network, a 4G network, a 5G network, another type of cellularnetwork, etc.), a public land mobile network (PLMN), a local areanetwork (LAN), a wide area network (WAN), a metropolitan area network(MAN), a telephone network (e.g., the Public Switched Telephone Network(PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 2 areprovided as an example. In practice, there can be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 2. Furthermore, two or more devices shown in FIG. 2 can beimplemented within a single device, or a single device shown in FIG. 2can be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 200 can perform one or more functions described as beingperformed by another set of devices of environment 200.

FIG. 3 is a diagram of example components of a device 300. Device 300can correspond to user device 210 and/or server device 220. In someimplementations, user device 210 and/or server device 220 can includeone or more devices 300 and/or one or more components of device 300. Asshown in FIG. 3, device 300 can include a bus 310, a processor 320, amemory 330, a storage component 340, an input component 350, an outputcomponent 360, and a communication interface 370.

Bus 310 includes a component that permits communication among thecomponents of device 300. Processor 320 is implemented in hardware,firmware, or a combination of hardware and software. Processor 320includes a central processing unit (CPU), a graphics processing unit(GPU), an accelerated processing unit (APU), a microprocessor, amicrocontroller, a digital signal processor (DSP), a field-programmablegate array (FPGA), an application-specific integrated circuit (ASIC), oranother type of processing component. In some implementations, processor320 includes one or more processors capable of being programmed toperform a function. Memory 330 includes a random access memory (RAM), aread only memory (ROM), and/or another type of dynamic or static storagedevice (e.g., a flash memory, a magnetic memory, and/or an opticalmemory) that stores information and/or instructions for use by processor320.

Storage component 340 stores information and/or software related to theoperations and use of device 300. For example, storage component 340 caninclude a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, and/or a solid state disk), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 350 includes a component that permits device 300 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 350 caninclude a sensor for sensing information (e.g., a global positioningsystem (GPS) component, an accelerometer, a gyroscope, and/or anactuator). Output component 360 includes a component that providesoutput information from device 300 (e.g., a display, a speaker, and/orone or more light-emitting diodes (LEDs)).

Communication interface 370 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 300 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 370 can permit device 300to receive information from another device and/or provide information toanother device. For example, communication interface 370 can include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency (RF) interface, a universal serialbus (USB) interface, a Wi-Fi interface, a cellular network interface, orthe like.

Device 300 can perform one or more processes described herein. Device300 can perform these processes in response to processor 320 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 330 and/or storage component 340. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions can be read into memory 330 and/or storagecomponent 340 from another computer-readable medium or from anotherdevice via communication interface 370. When executed, softwareinstructions stored in memory 330 and/or storage component 340 can causeprocessor 320 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry can be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 3 are provided asan example. In practice, device 300 can include additional components,fewer components, different components, or differently arrangedcomponents than those shown in FIG. 3. Additionally, or alternatively, aset of components (e.g., one or more components) of device 300 canperform one or more functions described as being performed by anotherset of components of device 300.

FIG. 4 is a flow chart of an example process 400 for a predictiveintersection search. In some implementations, one or more process blocksof FIG. 4 can be performed by server device 220. In someimplementations, one or more process blocks of FIG. 4 can be performedby another device or a group of devices separate from or includingserver device 220, such as user device 210.

As shown in FIG. 4, process 400 can include receiving, from a userdevice, input indicating an intersection of two or more roads associatedwith a search for the intersection (block 410). For example, serverdevice 220 can receive, from user device 210, input indicating anintersection of two or more roads associated with a search for theintersection (e.g., on a map).

In some implementations, server device 220 can receive the inputperiodically, according to a schedule, based on a user of user device210 inputting information into user device 210, based on server device220 requesting the information, and/or the like. In someimplementations, the input can include text input, voice input, and/orthe like. In some implementations, the input can include an incompleteaddress of an intersection. For example, the input can include portionsof identifiers that identify the two or more roads. Continuing with theprevious example, the input can include “16 and b” rather than “16thStreet and Blake Street, Anywhere, CO, 22222,” where “16” is a portionof an identifier of a first road associated with an intersection and “b”is a portion of an identifier of a second road associated with theintersection.

In some implementations, server device 220 can receive informationrelated to a geographic location of user device 210. For example, serverdevice 220 can receive information identifying a GPS location of userdevice 210, an address associated with an account associated with userdevice 210, input from the user of user device 210, and/or the like. Asother examples, server device 220 can receive information related toother searches of a user of user device 210, information related toother searches by users of other user devices 210, information thatidentifies landmarks, and/or the like (e.g., from user device 210, fromanother server device 220, from memory resources of server device 220,etc.).

In some implementations, server device 220 can receive the informationin real-time. For example, server device 220 can receive the informationas a user of user device 210 is inputting the input to user device 210.In some implementations, server device 220 can receive the informationwhen the user inputs a particular term, symbol, and/or the like (e.g.,when the user inputs the term “and” indicating that the user isinputting information that identifies an intersection). This conservesprocessing resources of user device 210 and/or server device 220 bypreventing user device 210 from providing input for a search for anintersection to server device 220 until a user inputs a particular term,symbol, and/or the like that indicates a search for an intersection.

In this way, server device 220 can receive input indicating anintersection of two or more roads associated with a search for theintersection to permit server device 220 to identify the two or moreroads.

As further shown in FIG. 4, process 400 can include identifying the twoor more roads included in the input using one or more indicators in theinput that separate information identifying the two or more roads (block420). For example, server device 220 can identify the two or more roadsincluded in the input using one or more indicators in the input thatseparate information identifying the two or more roads. In someimplementations, server device 220 can identify the two or more roadsafter receiving the input.

In some implementations, the one or more indicators can include a term,a symbol, and/or the like. For example, the one or more indicators caninclude “and,” “&,” “@” “+” “X,” a term and/or symbol used in a languageother than English (e.g., a term and/or symbol in another language thatis similar to the previously described terms and/or symbols), and/or thelike. This increases a flexibility of a search for an intersection bypermitting a user of user device 210 to input a variety of indicatorsrelated to identifying an intersection.

In some implementations, server device 220 can use the one or moreindicators to identify the two or more roads. For example, server device220 can parse the input to identify the one or more indicators and candetermine that input separated by the one or more indicators identifiesthe two or more roads. As a particular example, server device 220 canparse the input “16 and b” into the terms “16,” “and,” and “b.” In thiscase, server device 220 can identify “and” as an indicator and canidentify “16” and “b” as identifying two roads associated with anintersection based on being separated by the indicator “and.” In someimplementations, server device 220 can parse the input using textanalysis, natural language processing, computational linguistics, and/orthe like.

In this way, server device 220 can identify the two or more roadsincluded in the input using one or more indicators in the input thatseparate information identifying the two or more roads.

As further shown in FIG. 4, process 400 can include determining ageographic location of the user device using information received fromthe user device (block 430). For example, server device 220 candetermine a geographic location of user device 210 using informationreceived from user device 210.

In some implementations, server device 220 can determine a GPS locationof user device 210, a latitude and longitude of user device 210, ageographic region of user device 210, an address associated with anaccount associated with user device 210, location of a base station orwireless access point to which user device 210 is connected, and/or thelike when determining a geographic location of user device 210. In someimplementations, server device 220 can determine the geographic locationusing geographic information received from user device 210.Additionally, or alternatively, server device 220 can determine ageographic location by performing a look up of information related touser device 210 in a data structure, identifying a city in which userdevice 210 is located using latitude and longitude information receivedfrom user device 210, and/or the like.

In some implementations, user device 210 can determine a geographiclocation when user device 210 is moving. For example, server device 220can determine an average latitude and longitude of user device 210during a threshold amount of time, determine whether user device 210 iswithin city limits of a city (e.g., based on an average latitude andlongitude of user device 210), a direction of travel of user device 210,a geographic location toward which user device 210 is moving, and/or thelike.

In this way, server device 220 can determine a geographic location ofuser device 210 using information received from user device 210, topermit identification of a data structure that identifies a set ofintersections associated with the geographic location of user device210.

As further shown in FIG. 4, process 400 can include identifying a datastructure that includes information identifying a set of intersectionsassociated with the geographic location (block 440). For example, serverdevice 220 can identify a data structure that includes informationidentifying a set of intersections associated with the geographiclocation of user device 210. In some implementations, a data structurecan include a resource for storing information, a database, a file(e.g., a computer resource for recording data in a computer storagedevice, such as server device 220 and/or memory resources of serverdevice 220), memory resources of user device 210 and/or server device220, and/or the like. In some implementations, a data structure can beassociated with a geographic location (e.g., a range of latitudes andlongitudes, a city, a state, a region, a coverage area of a basestation, etc.).

In some implementations, server device 220 can use informationidentifying a geographic location of user device 210 to perform a lookupwhen identifying a data structure. For example, server device 220 canperform a lookup of information identifying a geographic location in adata structure that includes information identifying various geographiclocations and corresponding data structure identifiers. In this case,server device 220 can identify a data structure when a result ofperforming the lookup indicates a match. In some implementations,identifying a data structure associated with a geographic location canconserve processing resources of server device 220 when server device220 performs a search by reducing an amount of information server device220 needs to process when performing a search. In addition, searchinginformation identifying intersections associated with a particulargeographic location permits server device 220 to identify more accurateresults (e.g., relative to a search of information identifyingintersections without consideration of a geographic location of userdevice 210).

In this way, server device 220 can identify a data structure thatincludes information identifying a set of intersections associated withthe geographic location of user device 210, thereby permitting serverdevice 220 to perform a search using information included in the datastructure.

As further shown in FIG. 4, process 400 can include performing a searchof the two or more roads using the information identifying the two ormore roads and the information included in the data structure to performthe search for the intersection (block 450). For example, server device220 can perform a search of the two or more roads using the informationidentifying the two or more roads and the information included in thedata structure to perform the search for the intersection (e.g.,identify the intersection). In some implementations, a search caninclude a prefix match search, an exact match search, a case insensitiveexact match search, a case insensitive prefix match search, a substringmatch search, a subsequence match search, and/or the like.

In some implementations, server device 220 can identify an intersectionidentified in the data structure where information identifying two ormore roads associated with the intersection matches informationidentifying the two or more roads in the input (e.g., by performing alookup of information identifying the two or more roads included in theinput in the data structure, processing the data structure usinginformation identifying the two or more roads included in the input,performing a comparison of information, etc.). For example, serverdevice 220 can perform the search of the two or more roads and canidentify one or more results where information identifying the two ormore roads matches information identifying the roads associated with theset of intersections.

Continuing with the previous example, server device 220 can perform aprefix match search of a first road identified in the input and a prefixmatch search of a second road identified in the input and can identifyan intersection where a result of both prefix match searches indicates amatch. Continuing still with the previous example, if the input includes“16” and “b” as identifying two roads, server device 220 can perform aprefix match search to identify intersections where an identifier of afirst road associated with an intersection begins with “16” and where anidentifier of a second road associated with an intersection begins with“b.”

In this case, server device 220 can identify an intersection when aresult of the search indicates a match for both “16” and “b.” In thisway, server device 220 can perform a search for an intersection using adata structure that includes information identifying intersectionsassociated with a geographic location. In addition, in this way, serverdevice 220 can perform a single search for an intersection (e.g., asingle search for the two or more roads) without needing to performindividual searches for each of the roads for the geographic locationand/or without needing to determine whether roads identified in theinput actually intersect, thereby improving an efficiency of performinga search for an intersection and conserving processing resources ofserver device 220 via a reduced quantity of operations that serverdevice 220 has to perform.

In some implementations, server device 220 can perform a search for allintersections identified in the data structure (e.g., rather thanterminating the search when the first match is identified). This canresult in server device 220 identifying multiple potential intersectionsthat match the user's input. This improves results that are provided touser device 210 for display by providing a set of results from which auser of user device 210 can make a selection.

In some implementations, server device 220 can perform a search ofparticular intersections not associated with the geographic location ofuser device 210. For example, server device 220 can perform a search forinformation identifying intersections designated as landmarks,intersections for which a threshold quantity of users have previouslysearched, and/or the like. In some implementations, server device 220can include information identifying an intersection not associated withthe geographic location of user device 210 in a search result when asearch indicates a match. This improves results of a search bypermitting server device 220 to identify potentially relevant resultsthat are not associated with a geographic location of user device 210(e.g., relative to a search for an intersection that is limited to ageographic location of a user of user device 210), thereby conservingprocessing resources that would otherwise be consumed due to lessaccurate results.

In this way, server device 220 can perform a search of the two or moreroads using the information identifying the two or more roads and theinformation included in the data structure to perform the search for theintersection.

As further shown in FIG. 4, process 400 can include determining apriority for one or more results of the search for the intersection(block 460). For example, server device 220 can determine a priority forone or more results of the search for the intersection (e.g., one ormore intersections where information identifying roads associated withthe one or more intersections matches input from user device 210). Insome implementations, server device 220 can determine a priority for oneor more results of the search after performing the search.

In some implementations, server device 220 can determine a prioritybased on prior searches of a user of user device 210. For example,server device 220 can determine a higher priority for a first identifiedintersection relative to a second identified intersection when a user ofuser device 210 has previously searched for the first identifiedintersection. In some implementations, server device 220 can determine apriority based on prior searches of other users of other user devices210. For example, server device 220 can determine a higher priority fora first identified intersection relative to a second identifiedintersection based on a threshold quantity of other users searching forthe first identified intersection, based on more users searching for thefirst identified intersection relative to the second identifiedintersection, and/or the like.

Additionally, or alternatively, server device 220 can determine apriority based on a geographic location of user device 210 relative toidentified intersections. For example, server device 220 can determine ahigher priority for a first identified intersection relative to a secondidentified intersection based on the first identified intersection beingphysically closer to the geographic location of user device 210 relativeto the second identified intersection. Additionally, or alternatively,and as another example, server device 220 can determine a higherpriority for a first identified intersection relative to a secondidentified intersection based on the user, or other users of other userdevices 210, having performed a threshold quantity of searches forlocations within a threshold distance of the first identifiedintersection.

Additionally, or alternatively, server device 220 can determine apriority based on a direction of travel of user device 210. For example,if server device 220 determines that user device 210 is travelling in aparticular direction (e.g., using GPS information from user device 210),server device 220 can determine a higher priority for a first identifiedintersection relative to a second identified intersection based on thefirst identified intersection being in the same direction in which userdevice 210 is travelling.

Additionally, or alternatively, and as another example, server device220 can determine a higher priority for a first identified intersectionrelative to a second identified intersection based on the firstidentified intersection being identified as a landmark, or other type oflocation, in the data structure (e.g., a tourist destination, a shoppingdistrict, etc.). For example, a first identified intersection within athreshold distance of a historical location or a tourist area canreceive a higher priority relative to a second identified intersection,even if the first identified intersection is in a geographic locationdifferent than user device 210. As a particular example, for a searchfor “broadway and seventh avenue,” server device 220 can prioritizeBroadway and Seventh Avenue in New York City, N.Y. (Times Square) higherthan another intersection of a Broadway and Seventh Avenue in anothergeographic location that is geographically closer to user device 210based on Times Square being identified as a popular tourist destinationin the data structure.

Additionally, or alternatively, and as another example, server device220 can determine a higher priority for a first identified intersectionrelative to a second identified intersection based on a score associatedwith the first identified intersection. For example, server device 220can determine a score for identified intersections based on acombination of the above described factors (e.g., where a factor thatindicates a higher priority receives a higher score) and can prioritizea set of identified intersections based on corresponding scores for theset of intersections.

In this way, server device 220 can determine a priority for one or moreresults of the search prior to providing the one or more results to userdevice 210.

As further shown in FIG. 4, process 400 can include providing the one ormore results of the search for the intersection ordered by the priorityto permit and/or cause an action to be performed (block 470). Forexample, server device 220 can provide the one or more results of thesearch ordered by the priority to permit and/or cause an action to beperformed (e.g., ordered from highest priority to lowest priority,grouped by various threshold priorities, etc.).

In some implementations, server device 220 can provide the one or moreresults to permit selection of an intersection from the one or moreresults (e.g., to cause server device 220 to determine a set ofdirections to a selected intersection). Additionally, or alternatively,server device 220 can provide the one or more results for display on amap. Additionally, or alternatively, server device 220 can determine aset of directions to the intersection. For example, server device 220can determine a set of directions from a current location of user device210 to the intersection. Additionally, or alternatively, server device220 can provide a set of instructions to a vehicle (e.g., an autonomousvehicle) to cause the vehicle to travel to the intersection.Additionally, or alternatively, server device 220 can receive a userselection from the one or more results. In some implementations, serverdevice 220 can store information identifying a user selection to permitserver device 220 to improve future search results, to reduce oreliminate a need for server device 220 to perform the same search forthe same user or a different user, and/or the like.

In some implementations, server device 220 can provide a determined setof directions to user device 210 for display (e.g., on a map).Additionally, or alternatively, server device 220 can open anapplication on user device 210 so that the application can provide a setof directions to the intersection for display via user device 210.Additionally, or alternatively, server device 220 can select anintersection from a set of intersections for which to generate a set ofdirections. For example, server device 220 can select an intersectionwith the highest score relative to other intersections when the scorefor the intersection satisfies a threshold. Additionally, oralternatively, when scores for a set intersections fail to satisfy athreshold, server device 220 can provide information identifying the setof intersections for display via user device 210 to permit a user ofuser device 210 to select a particular intersection.

Additionally, or alternatively, server device 220 can provideinformation related to locations within a threshold distance of anintersection for display via user device 210. For example, server device220 can provide information related to landmarks, tickets for events,coupons, show times, and/or the like for locations within a thresholddistance of an intersection. Additionally, or alternatively, serverdevice 220 can generate a post on a social media website that identifiesan intersection to which a user of user device 210 is travelling, anestimated arrival time for arriving at an intersection, and/or the like.

Additionally, or alternatively, server device 220 can perform additionalsearches as the user provides additional input or modifies previouslyprovided input (e.g., in real-time). In some implementations, serverdevice 220 can modify the one or more results provided to user device210. For example, server device 220 can update a priority of searchresults provided to user device 210 (e.g., based on a direction oftravel of user device 210, based on other users of other user devices210 performing searches for various intersections, etc.).

In this way, server device 220 can provide the one or more searchresults of the search ordered by priority to permit and/or cause anaction to be performed.

Although FIG. 4 shows example blocks of process 400, in someimplementations, process 400 can include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 4. Additionally, or alternatively, two or more of theblocks of process 400 can be performed in parallel.

Some implementations, described herein, provide a server device that iscapable of searching for an intersection using input that includes anincomplete address for the intersection (e.g., “16 and Blake,” “16th andBlake st,” “16 and B,” etc. rather than “16th street and Blake street,Anywhere, CO, 22222”). In addition, the server device can prioritizesearch results based on various factors. In this way, the server devicecan dynamically and predictively perform a search for an intersection.This conserves processing resources of the server device by increasing aflexibility of the server device to perform a search for an intersectionusing an incomplete address of the intersection. In addition, thisconserves time of the user related to performing a search for anintersection and/or increases an efficiency of performing a search foran intersection by permitting use of an incomplete address for theintersection. Further, this increases an efficiency of performing asearch for an intersection by reducing an amount of information theserver device processes and/or searches to perform the search, therebyconserving processing resources of the server device.

Further, this increases an accuracy of performing a search for anintersection via prioritization of search results based on variousfactors. Further, the device can perform a search for an intersectionwithout needing to perform individual searches for each of the roads todetermine whether the roads are associated with a geographic locationand/or to determine whether roads identified in the input actuallyintersect, thereby improving an efficiency of performing a search for anintersection and conserving processing resources of the device byreducing or eliminating a need for the server device to performparticular operations related to performing a search for anintersection.

The foregoing disclosure provides illustration and description, but isnot intended to be exhaustive or to limit the implementations to theprecise form disclosed. Modifications and variations are possible inlight of the above disclosure or can be acquired from practice of theimplementations.

As used herein, the term component is intended to be broadly construedas hardware, firmware, or a combination of hardware and software.

Some implementations are described herein in connection with thresholds.As used herein, satisfying a threshold can refer to a value beinggreater than the threshold, more than the threshold, higher than thethreshold, greater than or equal to the threshold, less than thethreshold, fewer than the threshold, lower than the threshold, less thanor equal to the threshold, equal to the threshold, etc.

To the extent the aforementioned embodiments collect, store, or employpersonal information provided by individuals, it should be understoodthat such information shall be used in accordance with all applicablelaws concerning protection of personal information. Additionally, thecollection, storage, and use of such information can be subject toconsent of the individual to such activity, for example, through wellknown “opt-in” or “opt-out” processes as can be appropriate for thesituation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

It will be apparent that systems and/or methods, described herein, canbe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of possible implementations. In fact,many of these features can be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below can directly depend on only one claim, thedisclosure of possible implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and can be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and can be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

1. What is claimed is:
 1. A method, comprising: receiving, by a device, an input; identifying, by the device and based on the input, two or more roads or prefixes associated with the two or more roads; performing, by the device and based on identifying the two or more roads or the prefixes, a search for an intersection using information identifying the two or more roads or the prefixes; and providing, by the device and for display on a map, one or more results of the search to permit or cause one or more actions to be performed, the one or more results identifying one or more intersections, and the one or more actions including at least one of: selecting a particular intersection, of the one or more intersections, associated with the two or more roads, or determining a set of directions to the particular intersection.
 2. The method of claim 1, further comprising: determining a location of the device; and wherein determining the set of directions to the particular intersection comprises: determining the set of directions from the location of the device to the particular intersection.
 3. The method of claim 1, further comprising: providing the set of directions to a vehicle.
 4. The method of claim 1, wherein selecting the particular intersection comprises: selecting the particular intersection based on a user selection of a particular result of the one or more results.
 5. The method of claim 4, further comprising: storing information identifying the user selection to improve future search results.
 6. The method of claim 1, further comprising: providing, for display on the map, the set of directions.
 7. The method of claim 1, further comprising: causing an application to open; and providing, for display via the application, the set of directions.
 8. A device, comprising: one or more memories; and one or more processors communicatively coupled to the one or more memories, configured to: receive an input; identify, based on the input, two or more roads or portions of names associated with the two or more roads; perform a search for an intersection using information identifying the two or more roads or the portions of names; and provide, for display on a map, one or more results of the search to permit or cause one or more actions to be performed, the one or more results identifying one or more intersections, and the one or more actions including at least one of: a selection of a particular intersection, of the one or more intersections, associated with the two or more roads, or a determination of a set of directions to the particular intersection.
 9. The device of claim 8, wherein the one or more processors are further configured to: provide information related to at least one of a landmark or an event associated with a location within a threshold distance of the particular intersection.
 10. The device of claim 8, wherein the one or more processors are further configured to: receive an additional input; and modify the one or more results based on the additional input.
 11. The device of claim 8, wherein the input is a voice input.
 12. The device of claim 8, wherein the one or more processors are further configured to: determine a location of the device; and determine, based on the location, a priority for the one or more results.
 13. The device of claim 8, wherein the one or more processors, when receiving the input, are configured to: receive the input from another device; and wherein the one or more processors are further configured to: provide the set of directions to the other device.
 14. The device of claim 13, wherein the one or more processors are further configured to: cause an application to open on the other device, and the set of directions being provided, for display, via the application.
 15. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive an input; identify, based on the input, two or more roads or prefixes associated with the two or more roads; perform, based on identifying the two or more roads or the prefixes, a search for an intersection using information identifying the two or more roads or the prefixes; and provide, for display on a map, one or more results of the search to permit or cause one or more actions to be performed, the one or more results identifying one or more intersections, and the one or more actions including at least one of: select a particular intersection, of the one or more intersections, associated with the two or more roads, or determine a set of directions to the particular intersection.
 16. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: determine a location of a user device; and wherein the one or more instructions, that cause the one or more processors to determine the set of directions to the particular intersection, cause the one or more processors to: determine the set of directions from the location of the user device to the particular intersection.
 17. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: provide the set of directions to a vehicle.
 18. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions, that cause the one or more processors to select the particular intersection, cause the one or more processors to: receive a user selection of a particular result of the one or more results.
 19. The non-transitory computer-readable medium of claim 18, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: store information identifying the user selection to improve future search results.
 20. The non-transitory computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: cause an application to open; and provide, for display via the application, the set of directions. 